Exploratory Data Analysis - Happiness

This dataset has been taken from Kaggle.

We will be performing data cleaning, preparation and visualization on the World Happiness Report dataset.

The focus of this study will be to see:

Looks like there are missing values in some of the columns but since the missing values are less than 1% of the total column values we can move forward.

Looks like this dataset contains more columns than the one with mutiple years.
We will have to delete the extra columns as these are only present for 2021 and not all years.

Note : It can be seen that columns ( Positive affect & Negative affect) are not present in df_2021.

Great! All columns are filled to the trim!

Great! now our dataset is ready!

It is observed that most of the countries/states present in North American & ANZ and the Western European regions have maintained a high levels of happiness throughtout many years

We will see what were the factors leading to this!

Similarly, it can be observed that most of the countries present in Sub-Saharan African, Asian & Southeast Asian regions have happiness levels fluctuating between low to medium. Indicating a lower score happiness score throughout many years.

We will see what were the factors leading to this!

From the above graph we can see that Denmark has the highest mean happiness level scores throughtout all the years

We'll see what were the contributors that led to this!

From the above graph we can see that South Sudan has the lowest mean happiness level scores throughtout all the years

We'll see what were the contributors that led to this!

It seems that, GDP per capita score, Healthy life expectancy & Social Support of a country, are the main factors contributing to the overall happiness level!

Surprisingly, GDP score and Healthy life expectancy are most closely related! Let's see how!

It is observed that as the GDP per capita of a country increases, the healthy life expectancy of that country increases as well.

As seen in our first geo graph, most of the countries in The Sub-Saharan African region has a low GDP score and thus a low healthy life expectancy.

Conclusion :